Linked Lists

Linked lists are a fundamental data structure in computer science, used to store a collection of items in a sequential manner. Unlike arrays, linked lists store elements in separate objects called “nodes,” and each node contains a reference (or a “link”) to the next node in the sequence. This structure allows for efficient insertion and removal of elements without needing to reorganize the entire data structure, making linked lists a versatile choice for many algorithms and applications. In this blog, we’ll explore the basics of linked lists, their types, and provide simple examples to help you understand how they work.

What is a Linked List?

At its core, a linked list is a collection of nodes, where each node contains data and a reference (or pointer) to the next node in the list. The first node is called the head, and the last node, which points to null (indicating the end of the list), is known as the tail. This structure allows data to be stored in a flexible and efficient manner.

Why Use Linked Lists?

Linked lists offer several advantages over traditional arrays, including:

  • Dynamic Size: Unlike arrays, linked lists can easily grow or shrink in size, making them ideal for situations where the number of elements can change over time.
  • Efficient Operations: Adding or removing elements from a linked list is generally more efficient than doing so with an array, especially if the operation is near the beginning of the list, because it doesn’t require shifting elements.

However, linked lists also have some drawbacks, such as:

  • Sequential Access: Accessing an element in a linked list requires traversing from the head of the list to the desired node, which can be slower than indexed access in an array.
  • Extra Memory: Each element in a linked list requires extra memory for the reference (or pointer) to the next node.

Types of Linked Lists

  1. Singly Linked List: Each node contains data and a reference to the next node. This is the simplest form of a linked list.
  2. Doubly Linked List: Nodes contain a reference to both the next and the previous node, allowing for backward traversal of the list.
  3. Circular Linked List: The last node of the list points back to the first node, forming a circle.

Example: Implementing a Singly Linked List

Let’s implement a basic singly linked list in Python to illustrate how it works:

class Node:
    def __init__(self, data): = data = None

class LinkedList:
    def __init__(self):
        self.head = None

    def append(self, data):
        new_node = Node(data)
        if not self.head:
            self.head = new_node
        last_node = self.head
            last_node = = new_node

    def print_list(self):
        cur_node = self.head
        while cur_node:
            print(, end=" -> ")
            cur_node =

In this example, the LinkedList class manages the list, and the Node class represents each element in the list. To add an element, we create a new node and traverse the list until we reach the end, then link the new node to the last node in the list. The print_list method allows us to visualize the list by printing each element’s data followed by an arrow pointing to the next element, ending with “None” to indicate the end of the list.

Working with the Linked List

Here’s how you can use the above implementation to create a linked list and add some elements:

# Create a new linked list
my_list = LinkedList()

# Append elements

# Print the list
# Output: 1 -> 2 -> 3 -> None


Linked lists are a powerful and flexible data structure that can handle dynamic data sets efficiently. By understanding the basic concepts and operations of linked lists, you can start to leverage their capabilities in your algorithms and applications. Whether you’re implementing a singly, doubly, or circular linked list, the principles remain the same, offering a foundation for more complex data structures and algorithms. As you continue your journey in learning data structures, experimenting with linked lists will provide valuable insights into the organization and manipulation of data.